Search Results (349)

The rapid diffusion of electric vehicles (EVs) is reshaping mobility markets and creating new opportunities for embedded financial services. This study examines consumer acceptance of embedded EV insurance, which refers to coverage bundled directly at the point of vehicle sale in Taiwan, China. Using survey data from 400 licensed drivers, we analyze how demographic factors and five psychological drivers—perceived savings, convenience, trust, expected satisfaction, and fairness—shape the likelihood of choosing embedded insurance over traditional stand-alone policies. Welch’s t-tests show that younger drivers perceive greater savings and convenience, while older drivers express stronger fairness concerns. Logistic regression results indicate that convenience (OR = 2.05) and perceived savings (OR = 1.76) substantially increase adoption likelihood, whereas fairness concerns reduce it (OR = 0.71). Theoretically, this study advances consumer behavior research by demonstrating how functional value perceptions (convenience and savings) and fairness evaluations jointly influence decisions in digitally mediated insurance contexts. It also contributes to embedded finance theory by revealing how insurance embedded within EV purchasing ecosystems reshapes consumer decision processes and alters traditional insurer–consumer relationships. These findings offer strategic implications for automakers, insurers, and policymakers designing consumer-centric embedded financial products in emerging mobility markets. Full article

Creativity serves as a fundamental driver of human learning, personal development, and societal progress. This study synthesizes recent empirical and theoretical advances in educational psychology and creativity neuroscience to characterize the paradoxical nature of creative processes. We conceptualize creativity through three interdependent dimensions—novelty with usefulness, persistence alongside flexibility, and divergence in convergence—illuminating both its cognitive architecture and neurophysiological dynamics. By integrating evidence across levels, we bridge individual cognitive mechanisms with group dynamics and cultural contexts to propose actionable strategies for cultivating creativity. These findings offer critical insights into how these dimensions operate synergistically, informing the design of educational and applied interventions that promote sustained, adaptive creative development. Full article

This study investigates how emotionally structured online interaction networks shape consumer perception of new energy vehicle (NEV) technology. Drawing on discussion forum data from two leading NEV brands, Brand_T and Brand_B, we focus on how users respond to brand technological narratives and how these responses translate into distinct patterns of peer-to-peer interaction. Using a behavioral network analysis framework, we integrate sentiment analysis, topic modeling, and Exponential Random Graph Modeling (ERGM) to uncover the psychological and structural mechanisms underlying consumer engagement. Three main findings emerge. First, users display brand-specific emotional-cognitive profiles: Brand_T communities show broader technological engagement but more heterogeneous emotional responses, whereas Brand_B communities exhibit more emotionally aligned discussions. Second, emotional homophily is a robust driver of interaction ties, particularly in Brand_B forums, where positive sentiment clusters into dense and supportive discussion subnetworks. Third, perceived technological benefits, rather than risk sensitivity, are consistently associated with higher interaction intensity, underscoring the motivational salience of anticipated gains over cautionary concerns in shaping engagement behavior. The study contributes to behavioral science and transportation behavior research by linking consumer sentiment, cognition, and social interaction dynamics in digital environments, offering an integrated theoretical account that bridges the Elaboration Likelihood Model, social identity processes, and behavioral network formation. This advances the understanding of technology perception from static individual evaluations to dynamic, group-structured outcomes. It highlights how emotionally patterned interaction networks can reinforce or recalibrate technology-related perceptions, offering practical implications for NEV manufacturers and policymakers seeking to design psychologically informed communication strategies that support sustainable technology adoption. Full article

Medical students experience fluctuations in their motivation, influenced by various factors, including curricular rigor, mental health, and institutional factors. Based on Self-Determination Theory (SDT) and the Four Pillars of Academic Engagement (HPEE), this study, conducted at a private Mexican university, examined motivational variation according to academic year, curricular impact, gender differences, and its relationship with mental health. Methods: A quantitative, cross-sectional, descriptive study was conducted using qualitative tools for contextualization (n = 1326). Mann–Whitney U tests, Kruskal–Wallis tests, logistic regression, and psychological network analysis were performed. Results: Motivation showed cross-sectional variation: high in preclinical years 1 and 2, decreasing in clinical years 3 and 4 (p < 0.001), and rebounding in year 6. The reformed curriculum (elective subjects, student-centered active learning) resulted in greater motivation (OR = 10.68, p < 0.001). Women tended to have slightly higher motivation (p = 0.050), higher grade point averages (p < 0.001), but also greater stress (p < 0.001). Network analysis revealed that intrinsic achievement (centrality = 1.11) and curiosity about knowledge (predictability = 84.5%) are the main drivers, while demotivation was linked to the later years. The qualitative part of the study showed altruism/curiosity as the main motivators; mistreatment/workload (demotivators). Conclusions: Motivation is context-sensitive, peaks in the preclinical stage, and recovers with autonomy but is vulnerable during clinical immersion. Autonomy in course selection, active student-centered pedagogies, and gender-sensitive support foster sustained participation. The centrality of intrinsic factors in the network highlights that achievement motivation and knowledge are general and independent motivators. Qualitative data reveal systemic barriers. Stage-specific interventions, such as mentoring, student support programs, and reporting mistreatment, can be crucial for strengthening resilience and performance. Longitudinal and multi-institutional studies are needed to validate the causality and generalizability of this study. Full article

This study examines the psychological mechanisms underlying service stickiness during the mature phase of the AI subscription economy, with particular attention to the paradox of subscription fatigue. To enhance conceptual clarity, AI-driven stimuli—specifically Algorithmic Curation and Technological Fluidity—are defined as perceived attributes at the individual level. Employing the Stimulus–Organism–Response (S-O-R) framework, the research explores how these perceived stimuli influence consumers’ internal states (Cognitive Efficiency and Serendipity) and subsequent behavioral responses (Service Stickiness). Empirical analysis using partial least squares structural equation modeling (PLS-SEM) on data from U.S. subscription service users yields several theoretical insights. Cognitive Efficiency is identified as the primary driver of stickiness, indicating that, in the context of subscription fatigue, the utilitarian benefit of reduced cognitive effort surpasses hedonic enjoyment. Additionally, the study identifies a “Frictionless Trap,” in which excessive Technological Fluidity negatively affects Serendipity (β = −0.195), suggesting that an entirely seamless experience may create a filter bubble that limits unexpected discovery. As a result, Serendipity does not significantly affect stickiness in the aggregate model. However, post hoc analysis demonstrates that Serendipity remains significant for high-income users, while Cognitive Efficiency is most influential in high-frequency utilitarian contexts, such as food services. These findings indicate that sustainable retention depends on reducing cognitive load while intentionally introducing friction to preserve opportunities for discovery. Full article

Severe emotional stress constitutes a significant public-health concern associated with negative health outcomes. Although the clinical effects are well acknowledged, the specific biological mechanisms that translate emotional suffering into systemic disease remain incompletely understood. Psychological stress activates the sympathetic nervous system and hypothalamic–pituitary–adrenal axis, which directly target mitochondria and alter their bioenergetic and redox capacity. For this reason, this narrative review proposes that mitochondria serve as the primary subcellular link in the mind–body connection, as they play a pivotal role in converting neuroendocrine signals into cellular dysfunction. In particular, we focus on the concept of mitochondrial allostatic load (MALT), a framework explaining how the progressive decline in mitochondrial functions, from their initial adaptive roles in energy production, reactive oxygen species signaling, and calcium regulation, to being sources of inflammation and systemic damage, occurs when stress exceeds regulatory limits. We also, discuss how this transition turns mitochondria from adaptive responders into drivers of multi-organ disease. In subsequent sections, we examine diagnostic potentials related to MALT, including the use of biomarkers, such as growth differentiation factor 15, cell-free mitochondrial desoxyribonucleic acid, and functional respirometry. Furthermore, we evaluate mitochondria-targeted therapeutic strategies, encompassing pharmacological compounds, such as mitoquinone mesylate, Skulachev ions, and elamipretide, alongside lifestyle and psychological interventions. Here, we aim to translate MALT biology into clinical applications, positioning mitochondrial health as a target for preventing and treating stress-related disorders. We propose that MALT may serve as a quantifiable bridge between emotional stress and somatic disease, enabling future precision medicine strategies integrating mitochondrial care. Full article

Equine yards represent a substantial yet often overlooked land-use category in Europe, with potential to contribute to biodiversity and environment conservation. This study explored behavioral drivers and barriers to biodiversity implementation on Dutch equine yards using the COM-B model (Capability, Opportunity, Motivation—Behavior). Semi-structured interviews were conducted with 19 yard owners, covering both private and commercial operations ranging from <3 hectares to >3 hectares. Data were analyzed thematically using a deductive COM-B framework, with coded responses quantified to assess the relative weight of barriers and enablers. Reflective motivation emerged as a consistent enabler, grounded in values such as equine welfare, sustainability, and responsible land use. However, barriers were more prevalent overall, particularly within physical and social opportunity. Small yards faced constraints related to time, labor, and land tenure, while larger yards reported challenges integrating biodiversity into routines and navigating regulatory complexity. Psychological capability was not a major constraint, though yard owners expressed a clear need for externally sourced, informed advice. These findings suggest that while motivation is high, structural barriers limit implementation. Unlocking the ecological potential of equine yards will require targeted, size-sensitive policy support, recognition of their land stewardship role, and better integration of biodiversity into daily management practices. Full article

The research elaborates on and empirically verifies an integrative model that describes how the combination of various workplace resources results in the improvement of employee and organizational outcomes. It is based on the Job Demands–Resources model and the Resource-Based View to conceptualize Employee Experience Capital (EEC) as a higher-order construct, consisting of seven interrelation drivers, including digital autonomy, inclusive cognition, sustainability alignment, AI synergy, mindful design, learning agility, and wellness technology. This study examines the effect of these resources in developing two psychological processes, work resonance and employee vitality, which subsequently improves organizational performance. It also examines how the well-being of employees can be a contextual moderator that determines such relationships. The study, based on a cross-sectional design and the diversified sample of the employees who work in various digitally transformed industries, proves that EEC is a great way to improve resonance and vitality, which are mutually complementary mediators between resource bundles and performance outcomes. Employee well-being turns out to be a factor of performance, as opposed to a circumscribed condition. The results put EEC as one of the strategic types of human capital that values digital, sustainable, and wellness-oriented practices to employee well-being and sustainable organizational performance and provides new theoretical contributions and practical guidance to leaders striving to create resource-rich, high-performing workplaces. Full article

In this study, we employ the PLS-SEM modelling approach to explore the socio-psychological drivers of horticulture, citrus, and table grapes Greek farmers to adopt biopesticides, beneficial insects, and/or functional biodiversity practices for pest control. Additionally, we investigate the barriers these farmers face-off when it comes to adoption. We found that overall “openness to innovation” and “general attitudes” have the most substantial, positive, and significant impact on farmers’ intentions for adoption. On the contrary, uncertainty, lack of financial support, and cost were identified as the three key main barriers. Importantly, our analysis emphasizes the need for tailored-made policies. Full article

In recent years, China has made strong national commitments to waste reduction and circular economy, including the implementation of mandatory municipal solid waste separation policies and the rollout of zero-waste city initiatives. These efforts represent a strategic shift toward systemic environmental governance. However, the outbreak of the COVID-19 pandemic in early 2020—and the subsequent implementation of the country’s stringent zero-COVID policy—led to an abrupt disruption of these programs. Under this policy, strict lockdowns, quarantine of both confirmed and suspected cases, and city-wide containment became top priorities, sidelining environmental initiatives such as waste separation and sustainable waste infrastructure development. This study investigates how Chinese residents’ motivations for waste separation evolved across three key phases: pre-pandemic, during the zero-COVID enforcement period, and post-pandemic recovery. Grounded in the Theory of Planned Behavior and pro-environmental behavior theory, we developed an extended model incorporating pandemic-related social, psychological, and policy variables. Based on 526 valid questionnaire responses collected in late 2023 in Shanghai, we conducted structural equation modeling and repeated-measures analysis. Findings reveal a significant shift from externally driven compliance—reliant on governmental enforcement and service provision—to internally motivated behavior based on environmental values and personal efficacy. This transition was most evident after the pandemic, suggesting the potential for sustained pro-environmental habits despite weakened policy enforcement. Our findings underscore the importance of strengthening internal drivers in environmental governance, especially under conditions where policy continuity is vulnerable to systemic shocks such as public health emergencies. Full article

COVID-19 lockdown announcements triggered global waves of panic buying, leading to widespread panic buying of essential goods and supply chain disruptions. Although the acute phase of the pandemic has passed, panic buying continues to emerge during natural disasters, extreme weather events, and other crisis-related disruptions, highlighting the ongoing need for evidence-based strategies to address its psychological drivers. Social cognition constructs, including willingness, intentions, attitudes, subjective norms, and risk perceptions, have been identified as modifiable psychological predictors of panic buying. However, few studies have experimentally tested theory-driven interventions aimed at modifying these mechanisms. This study evaluated the effectiveness of a brief, online intervention based on integrated social cognition models in reducing panic-buying-related cognitions during a hypothetical lockdown scenario. A pre-registered randomized controlled trial was conducted with Australian grocery shoppers (N = 140), who were randomly allocated to an intervention or control condition. Participants completed self-report measures assessing their willingness, intentions, attitudes, subjective norms, and risk perceptions at both pre- and post-intervention times. The hypotheses were partially supported. Compared with the control condition, the intervention group reported greater reductions across targeted psychological constructs. For hygiene products, significant decreases were observed across all five constructs, and for non-perishable foods, willingness, intention, and attitudes significantly decreased. For cleaning products, reductions were evident for attitudes, subjective norms, and intentions. These findings suggest that theory-informed, scalable interventions can effectively modify the social cognition processes underlying panic buying. This study extends existing research and demonstrates the potential for brief, theory-based communication strategies to reduce panic-buying-related cognitions. Future research should evaluate these interventions in real-world settings and explore mechanisms to target automatic cognitive processes. Full article

Background/Objectives: Body self-image interacts with young adults’ health behaviors in complex ways, yet its role in shaping supplement use is not well defined. This study examined young adults’ body self-image and their use of dietary supplements commonly marketed to enhance physique, fitness, and weight outcomes. Methods: College students (N = 122; 18–28 years) completed the Body Self-Image Questionnaire-Short Form to assess body self-image and answered three dichotomous questions related to general dietary (DS), performance-enhancing (PES), and weight-loss (WLS) supplement use. Student scores were calculated across nine psychological subscale groups and ranked as high, moderate, or low percentile within our study sample. Chi-square analyses examined supplement prevalence in student responses ranked within the highest and lowest tertiles; middle tertile data were excluded as part of the extreme-group design. All responses were included in the logistical regression analysis. Results: Higher scores for the Investment in Ideals and Health-Fitness Evaluation subscales observed significantly higher PES use; both subscales and the male gender were significant predictors of PES use. Higher scores for the Fatness Evaluation, Negative Affect, and Social Dependence subscales observed significantly higher WLS use; Fatness Evaluation and age were significant predictors of WLS use. Subscales were not significantly associated with general supplement use in chi-square or logistical regression analyses. Conclusions: Our findings suggest that internalized appearance ideals, emotional distress, and social approval pressures are linked to weight- and physique-driven supplement behaviors in college students. Targeted, inclusive campus wellness initiatives are needed to address psychological drivers of weight-management practices, including potentially high-risk supplement use. Full article

Early identification of students at risk for low academic confidence, poor problem-solving skills, or poor academic performance is crucial to achieving equitable and sustainable learning outcomes. This research presents a hybrid artificial intelligence (AI) framework that combines feature selection using a Random Forest (RF) algorithm with data classification via an Artificial Neural Network (ANN) to predict risks related to Academic Confidence and Problem-Solving Skills (ACPS) among higher education students. Three real-world datasets from Saudi universities were used: MSAP, EAAAM, and MES. Data preprocessing included Min–Max normalisation, class balancing using SMOTE (Synthetic Minority Oversampling Technique), and recursive feature elimination. Model performance was evaluated using five-fold cross-validation and a paired t-test. The proposed model (RF-ANN) achieved an average accuracy of 98.02%, outperforming benchmark models such as XGBoost, TabNet, and an Autoencoder–ANN. Statistical tests confirmed the significant performance improvement (p < 0.05; Cohen’s d = 1.1–2.7). Feature importance and explainability analysis using a Random Forest and Shapley Additive Explanations (SHAP) showed that psychological and behavioural factors—particularly study hours, academic engagement, and stress indicators—were the most influential drivers of ACPS risk. Hence, the findings demonstrate that the proposed framework combines high predictive accuracy with interpretability, computational efficiency, and scalability. Practically, the model supports Sustainable Development Goal 4 (Quality Education) by enabling early, transparent identification of at-risk students, thereby empowering educators and academic advisors to deliver timely, targeted, and data-driven interventions. Full article

This study investigates the drivers of green production practices among forest-cultivated ginseng growers in Jilin Province, China, by integrating the Theory of Planned Behavior (TPB) and the Technology–Organization–Environment (TOE) framework. Based on survey data from 369 households in the major production regions of Tonghua, Baishan, and Yanbian areas, an Ordered Probit model and a Light Gradient Boosting Machine (LGBM) algorithm are employed for cross-validation. The results indicate that growers’ cognitive traits (awareness of green production standards and ecological/quality safety) and willingness (acceptance of price premiums for green products) are the most stable and critical drivers. Policy incentives (e.g., certification subsidies and outreach) not only directly promote green practices but also exhibit synergistic effects through interactions with resource endowments and psychological cognition. Regional heterogeneity is evident: Tonghua shows policy–market co-drive, Baishan is dominated by ecological constraints and safeguard policies, while Yanbian relies more on education and individual resources. Accordingly, this study proposes a differentiated policy system based on diagnosis–intervention–evaluation to support the high-quality development of forest-cultivated ginseng industry and ecological-economic synergies. Full article

Purpose: The central research question of the study is how objective financial knowledge and subjective financial confidence interact and relate to digital financial behavior and the use of FinTech tools. By examining both objective knowledge refers to measured, test-based financial competence and subjective confidence denote self-assessed financial understanding, the research offers insight into the psychological and demographic drivers of FinTech use and perceived financial well-being. Design/methodology/approach: Based on the OECD’s 2023 international financial literacy survey, the study uses a nationally representative Hungarian sample. It employs non-parametric statistical methods, linear regression, and two-step cluster analysis. Three composite indicators, general digital activity, digital financial engagement frequency, perceived financial security were developed to measure general digital activity, frequency of digital financial engagement, and perceived financial security. Findings: Results reveal a moderate but significant correlation between actual and self-assessed financial knowledge. Men score higher on both measures, though self-assessment bias does not significantly differ by gender. Higher education and income levels are associated with stronger financial literacy and more frequent use of FinTech tools, while age correlates negatively. However, the accuracy of self-perception is not explained by these demographic factors. Cluster analysis identifies four distinct financial knowledge profiles and five consumer digital behavior types, revealing disparities in digital financial inclusion and confidence. Originality: This research contributes a multidimensional perspective on how consumer capabilities, attitudes, and digital behavior influence FinTech adoption. By integrating behavioral, demographic, and psychological factors, the study offers practical implications for targeted financial education and the design of inclusive, human-centered digital financial services—especially relevant for emerging European markets. Full article